Predicting the Specific Energy Consumption of Reverse Osmosis Desalination
Desalination is often considered an approach for mitigating water stress. Despite the abundance of saline water worldwide, additional energy consumption and increased costs present barriers to widespread deployment of desalination as a municipal water supply. Specific energy consumption (SEC) is a c...
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doaj-74d4b276b92e45f38367ee114e155a092020-11-24T21:47:24ZengMDPI AGWater2073-44412016-12-0181260110.3390/w8120601w8120601Predicting the Specific Energy Consumption of Reverse Osmosis DesalinationAshlynn S. Stillwell0Michael E. Webber1Department of Civil and Environmental and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USADepartment of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USADesalination is often considered an approach for mitigating water stress. Despite the abundance of saline water worldwide, additional energy consumption and increased costs present barriers to widespread deployment of desalination as a municipal water supply. Specific energy consumption (SEC) is a common measure of the energy use in desalination processes, and depends on many operational and water quality factors. We completed multiple linear regression and relative importance statistical analyses of factors affecting SEC using both small-scale meta-data and municipal-scale empirical data to predict the energy consumption of desalination. Statistically significant results show water quality and initial year of operations to be significant and important factors in estimating SEC, explaining over 80% of the variation in SEC. More recent initial year of operations, lower salinity raw water, and higher salinity product water accurately predict lower values of SEC. Economic analysis revealed a weak statistical relationship between SEC and cost of water production. Analysis of associated greenhouse gas (GHG) emissions revealed important considerations of both electricity source and SEC in estimating the GHG-related sustainability of desalination. Results of our statistical analyses can aid decision-makers by predicting the SEC of desalination to a reasonable degree of accuracy with limited data.http://www.mdpi.com/2073-4441/8/12/601desalinationgreenhouse gas emissionsmultiple linear regressionspecific energy consumptionstatistical analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ashlynn S. Stillwell Michael E. Webber |
spellingShingle |
Ashlynn S. Stillwell Michael E. Webber Predicting the Specific Energy Consumption of Reverse Osmosis Desalination Water desalination greenhouse gas emissions multiple linear regression specific energy consumption statistical analysis |
author_facet |
Ashlynn S. Stillwell Michael E. Webber |
author_sort |
Ashlynn S. Stillwell |
title |
Predicting the Specific Energy Consumption of Reverse Osmosis Desalination |
title_short |
Predicting the Specific Energy Consumption of Reverse Osmosis Desalination |
title_full |
Predicting the Specific Energy Consumption of Reverse Osmosis Desalination |
title_fullStr |
Predicting the Specific Energy Consumption of Reverse Osmosis Desalination |
title_full_unstemmed |
Predicting the Specific Energy Consumption of Reverse Osmosis Desalination |
title_sort |
predicting the specific energy consumption of reverse osmosis desalination |
publisher |
MDPI AG |
series |
Water |
issn |
2073-4441 |
publishDate |
2016-12-01 |
description |
Desalination is often considered an approach for mitigating water stress. Despite the abundance of saline water worldwide, additional energy consumption and increased costs present barriers to widespread deployment of desalination as a municipal water supply. Specific energy consumption (SEC) is a common measure of the energy use in desalination processes, and depends on many operational and water quality factors. We completed multiple linear regression and relative importance statistical analyses of factors affecting SEC using both small-scale meta-data and municipal-scale empirical data to predict the energy consumption of desalination. Statistically significant results show water quality and initial year of operations to be significant and important factors in estimating SEC, explaining over 80% of the variation in SEC. More recent initial year of operations, lower salinity raw water, and higher salinity product water accurately predict lower values of SEC. Economic analysis revealed a weak statistical relationship between SEC and cost of water production. Analysis of associated greenhouse gas (GHG) emissions revealed important considerations of both electricity source and SEC in estimating the GHG-related sustainability of desalination. Results of our statistical analyses can aid decision-makers by predicting the SEC of desalination to a reasonable degree of accuracy with limited data. |
topic |
desalination greenhouse gas emissions multiple linear regression specific energy consumption statistical analysis |
url |
http://www.mdpi.com/2073-4441/8/12/601 |
work_keys_str_mv |
AT ashlynnsstillwell predictingthespecificenergyconsumptionofreverseosmosisdesalination AT michaelewebber predictingthespecificenergyconsumptionofreverseosmosisdesalination |
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1725897163964153856 |